easy-agent-mem 0.6.0

CLI-first persistent memory for AI coding sessions with direct Obsidian note writing and local fallback storage.

agent-mem

Automatic context compression and persistent memory for AI coding agents.

agent-mem helps you keep long coding sessions coherent by capturing decisions, session context, and code signals in structured memory notes. It also generates Obsidian-friendly project graph docs so you can navigate architecture, decisions, blockers, and recent context quickly.

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Why Use agent-mem

• Preserve critical context between chats and sessions
• Reduce token waste from repeating project history
• Keep technical decisions and blockers traceable
• Generate a searchable Obsidian-native knowledge graph from code + memory

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Core Features

• Smart watch mode with file + git + idle detection
• One-paste handoff prompts (Groq-powered, optional)
• Obsidian-first storage with wiki-links and YAML frontmatter
• Local fallback mode (.agent-memory/) when Obsidian is not configured
• graph command to build project knowledge docs from code, memory, and chat context

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Installation

pip install easy-agent-mem

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Quick Start

agent-mem init
agent-mem configure-groq      # optional for enrich/watch handoff generation
agent-mem watch               # start automatic handoff mode

After initialization, use agent-mem status to verify storage mode, graph output readiness, and Groq configuration status.

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Knowledge Graph (agent-mem graph)

Generate Obsidian-native docs into agent-mem-output/:

agent-mem graph build

Use optional flags:

agent-mem graph build --compact
agent-mem graph build --enrich
agent-mem graph build --compact --enrich
agent-mem graph build --exclude-file-pattern "tests/*" --exclude-file-pattern "**/migrations/*.py"

Graph Flags

Flag	Description
--compact	Trims long concept/function lists and writes full lists to agent-mem-output/Full/
--enrich	Adds inferred concepts/relationships via Groq when available
--exclude-file-pattern	Excludes files by glob pattern; repeatable

Generated Files

• Index.md: dashboard and navigation entrypoint
• Code/*: files, classes, functions, and imports
• Decisions/*: extracted decision and blocker signals
• Sessions/recent-chats.md: active and recent context snippets
• Concepts.md: concept inventory with EXTRACTED / INFERRED labels
• Graph-Report.md: plain-language summary of graph generation

Open agent-mem-output/Index.md in Obsidian for full navigation and backlinks.

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Daily Workflow

agent-mem watch
agent-mem checkpoint --stdin
agent-mem prepare-next
agent-mem recall "current goal"
agent-mem graph build --compact

Use this flow to maintain continuity during active implementation and produce graph notes when you need a wider project snapshot.

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Commands Overview

Command	Description
agent-mem init	Configure storage mode and IDE instructions
agent-mem configure-groq	Set Groq API key and model configuration
agent-mem watch	Run automatic handoff watcher
agent-mem graph build	Build knowledge graph notes
agent-mem summarize	Save manual structured summary
agent-mem checkpoint	Update compact active handoff context
agent-mem prepare-next	Print starter block for a fresh chat
agent-mem recall <query>	Search saved memory
agent-mem status	Show storage, graph, and Groq configuration

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Storage Modes

Obsidian Mode

If Obsidian is configured, notes are written under:

• Memory/Agent-Mem/ for session and active context notes
• agent-mem-output/ for graph notes

Local Fallback Mode

If Obsidian is unavailable, memory is written to:

• .agent-memory/active.md
• .agent-memory/memory.md

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Troubleshooting

• If --enrich does not apply inferred content, run agent-mem status and verify Groq key/model configuration.
• If graph output is too large, use --compact.
• For large repos, exclude low-value paths with repeatable --exclude-file-pattern options.

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Project Links

• PyPI: easy-agent-mem
• GitHub: atharvavdeo/agent-mem

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License

MIT